Category: Progress Updates

Final Presentation Testing Bike Walkthrough Final Report

This week, we shifted focus toward real-world testing on the bike to evaluate how our adaptive audio responds during different ride conditions. The goal: determine what structure and sound design will work best for the final demo. ML Introduced a background InferenceService that runs machine learning on live sensor data (pitch, roll, yaw, g-force) using…

This week was especially exciting because we finally mounted our sensor pack onto the bike. We faced difficulties getting I2C running with our new PCB but after a software update modifying the pin layout everything is working as it should. Sensor Pack This is the top of our sensor pack. It contains the display, accelerometer…

This week, we focused on enhancing both the functionality and polish of the adaptive music bike app. Here’s what we accomplished: ML FMOD Hardware/App Once the PCB arrives we can finally begin testing on the bike and train the ML model.

This week, we made significant strides in both hardware tuning and software integration for the adaptive music bike system. The test version of the firmware was successfully updated to include three potentiometers, enabling real-time adjustment of the jump and drop detection thresholds. This allows for rapid fine-tuning during test rides without needing to reprogram the…

Example images of our rapid prototype used for the in-class presentation on 5/6/2025

This week, we focused on both hardware stabilization to enhance sensor reliability and prepare for machine learning. We hope to begin testing on the bike soon. Hardware Improvements: Software Updates: Next Steps:

Technical Breakthroughs Power & Performance Next Steps

1. Project Summary Music Bike aims to revolutionize the cycling experience by transforming rider actions into a dynamic, real-time musical journey. Using sensors mounted on the bicycle (measuring motion like speed, tilt, and G-force) connected via Bluetooth Low Energy (BLE) to an Android application, the system will adaptively manipulate music playback using the FMOD audio…